python - 使用 python 获取 Apple M1 处理器的处理器类型给我一个 Intel 处理器

Question

我有一台配备 M1 处理器的新款 MacBook Pro，它是基于 ARM 的处理器，当我尝试使用 python 编程语言获取我的设备的处理器类型时，它告诉我这是一个英特尔处理器“i386”!怎么会发生这种事。

代码:

*import platform

platform.processor()
Out[4]: 'i386'*

Answer 1

让我们从结论开始:

是，在Python3版本<= 3.9.1下是正确的，您可以通过 isapplesiliconready.com 查看此信息，表明Python版本大于3.9.1时支持m1芯片。正如您所说，您使用的是 Spyder IDE，它可能由 Anaconda 控制，目前还不支持 m1 芯片。

---

那么，为什么？

原因是Rosetta，遵循official link ，它向您展示了旧应用程序如何在 m1 芯片下运行，基本上您只需要知道大多数旧应用程序都在兼容模式下运行，除非开发人员发布了专门编写或优化的版本m1芯片。那么Rosstta做了什么？当您需要运行旧应用程序时，它只是假装您正在使用Intel芯片，因此，结果与Intel芯片相同。

---

如何解决此案？

灵感来自this answer ，虽然函数名变了，但是仍然可以用来解决这种情况，代码如下。

import cpuinfo

# Just get the manufacturer of the processors

manufacturer = cpuinfo.get_cpu_info().get('brand_raw')
# 'Apple M1 Pro'

arch = 'arm' if 'm1' in manufacturer.lower() else 'x86_64'

# You can get all the info through the `get_cpu_info_json()`, like below.

>>> cpuinfo.get_cpu_info_json()

{
  "python_version": "3.9.7.final.0 (64 bit)",
  "cpuinfo_version": [
    8,
    0,
    0
  ],
  "cpuinfo_version_string": "8.0.0",
  "arch": "X86_64",
  "bits": 64,
  "count": 10,
  "arch_string_raw": "x86_64",
  "brand_raw": "Apple M1 Pro",
  "hz_actual_friendly": "2.4000 GHz",
  "hz_actual": [
    2400000000,
    0
  ],
  "family": 6,
  "flags": [
    "acpi",
    "aes",
    "apic",
    "clflush",
    "clfsh",
    "cmov",
    "cx16",
    "cx8",
    "de",
    "ds",
    "dscpl",
    "dtes64",
    "dtse64",
    "est",
    "fpu",
    "fxsr",
    "htt",
    "lahf_lm",
    "mca",
    "mce",
    "mmx",
    "mon",
    "monitor",
    "msr",
    "mtrr",
    "pae",
    "pat",
    "pbe",
    "pclmulqdq",
    "pdcm",
    "pge",
    "pni",
    "popcnt",
    "pse",
    "pse36",
    "seglim64",
    "sep",
    "ss",
    "sse",
    "sse2",
    "sse3",
    "sse4.1",
    "sse4.2",
    "sse4_1",
    "sse4_2",
    "ssse3",
    "tm",
    "tm2",
    "tpr",
    "tsc",
    "vme",
    "vmx"
  ],
  "vendor_id_raw": "GenuineIntel",
  "hz_advertised_friendly": "2.5000 GHz",
  "hz_advertised": [
    2500000000,
    0
  ],
  "l2_cache_size": 65536,
  "l2_cache_line_size": 8192,
  "l2_cache_associativity": 8,
  "model": 44
}